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Where's the Real Bottleneck in Scientific Computing?

机译:科学计算的真正瓶颈在哪里?

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摘要

When I first started doing computational science in 1986, a new generation of fast, cheap chips had just ushered in the current era of low-cost supercomputers, in which multiple processors work in parallel on a single problem. Suddenly, it seemed as though everyone who took number crunching seriously was rewriting his or her software to take advantage of these new machines. Sure, it hurt—the compilers that translated programs to run on parallel computers were flaky, debugging tools were nonexistent, and thinking about how to solve problems in parallel was often like trying to solve a thousand crossword puzzles at once—but the potential payoff seemed enormous.
机译:当我于1986年首次开始进行计算科学时,新一代的快速,廉价芯片才迎来了当前的低成本超级计算机时代,在该时代,多个处理器可以在一个问题上并行工作。突然之间,似乎每个认真对待数字运算的人都在重写他或她的软件,以利用这些新机器。当然,这很痛苦—编译程序无法在并行计算机上运行的编译器很笨拙,调试工具不存在,并且思考如何并行解决问题通常就像试图一次解决一千个填字游戏一样—但是似乎有潜在的回报巨大。

著录项

  • 来源
    《American Scientist》 |2006年第1期|p.5-6|共2页
  • 作者

    Gregory V. Wilson;

  • 作者单位

    Room 3230, Bahen Centre for Information Technology, University of Toronto, Toronto, Ontario, M5S 2E4;

  • 收录信息 美国《科学引文索引》(SCI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自然科学总论;
  • 关键词

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